Goosto is a culturally-driven food discovery app powered by AI.
It helps users explore new ethnic cuisines and restaurants through personalized recommendations and cultural storytelling.
For restaurants, it's a tool to share their heritage, connect with authenticity-seeking diners, and craft their narrative and menu with AI support. The platform also suggests engaging content to enhance visibility within the community.
Envision and prototype a cognitive experience powered by Generative AI, designed to enhance user interactions within one of the following contexts: restaurant, cruises, airline, travel accomodation, travel experiences.
Goosto offers an integrated platform that combines cultural storytelling with personalized food discovery.
The AI agent helps the restaurant owner to build their story and menu with a conversational interface
The AI agent guides the client to discover the story of the restaurant and the culture behind the dishes
The user can see their journey through cultures and cuisines they have tried
Personalized suggestions by the AI agent based on the user's journey
Since we were asked to design an AI agent for a cognitive experience, we began our research by exploring how AI tools are currently integrated into restaurant operations.
At the same time, given the dual nature of the restaurant sector (serving both businesses and customers) we also focused on the client's perspective. We investigated recent trends to identify gaps or opportunities for innovation in customer experience.
To do so, we analyzed existing food discovery platforms and cultural storytelling applications, aiming to understand both current market trends and user behaviors.
While AI is increasingly present in the restaurant industry, its current application, is heavily weighted towards automating and optimizing operational efficiency. In terms of customer experience (CX), its role is mainly as a continuous CRM resource.
Dining experiences are evolving towards a greater appreciation for diverse culinary traditions. Demand for authentic cultural immersion has gone beyond just the food. Exploring new flavours and cuisines, has led to the flourishing and increased visibility of ethnic restaurants.
Source: Ethnic Food Market Data
Spread a survey and conducted interviews with restaurant owners and ethnic food enthusiasts to understand their needs and pain points in discovering and sharing cultural food experiences.
Through our interviews and survey analysis, we discovered that users are increasingly interested in authentic cultural experiences when dining out. Many participants expressed frustration with the lack of cultural context and storytelling in their dining experiences, highlighting an opportunity for our platform to bridge this gap.
After analyzing the customer journey, we defined the user archetypes and the end-to-end experience, considering the features to implement and the AI agent's personality, as well as how it should interact with users.
The scope of the platform was to have a minimalistic design, with a focus on the user experience and the cultural storytelling aspect through the AI agent.
To do so, we designed the interaction with the AI agent to be as engaging as possible, focusing on the vocal interaction and visual feedback in order to give the user a better sense of immersion into the story.
Practically, we created a set of guidelines for the design system, which included the color palette, the typography, the icons and the components.
Screen examples of the restaurateurs' side of the platform, where they can build their story and menu with the help of the AI agent.
Story Creation - 1
Story Creation - 2
Profile improvement suggestions
Screens examples of the cultural explorer's side of the platforms.
AI Agent
Restaurant details
Story view
Dish details
Journey
Because of the time constraints, we were not able to test the platform with real users. However, we did a usability test especially for the interaction with the AI agent with a few professors and professionals from Spark Reply.
During the course of the project, we also developed a business model and a marketing strategy for the platform.
Targets of our business:
We decided to target restaurants as paying users since they are the ones who would see benefits in the sense of reaching a wider audience more interested in their cuisine and culture.Also, in the last years they are willing more and more to invest in digital services to enhance their visibility and customer engagement.
Contribution margin: calculated by subtracting the variable costs (commissions of Apple Store on each subscription) from the revenue (weighted average of the two subscription levels).
Fixed cost per year (considering the first year of the project): staff costs (mainly developer and AI specialist), other costs (mainly marketing, depreciation, AI tokens).
Break-even point: calculated by dividing the fixed costs by the contribution margin.
